Reduced nucleus accumbens functional connectivity in reward network and default mode network in patients with recurrent major depressive disorder

Autor: Yu-Dan Ding, Xiao Chen, Zuo-Bing Chen, Le Li, Xue-Ying Li, Francisco Xavier Castellanos, Tong-Jian Bai, Qi-Jing Bo, Jun Cao, Zhi-Kai Chang, Guan-Mao Chen, Ning-Xuan Chen, Wei Chen, Chang Cheng, Yu-Qi Cheng, Xi-Long Cui, Jia Duan, Yi-Ru Fang, Qi-Yong Gong, Zheng-Hua Hou, Lan Hu, Li Kuang, Feng Li, Hui-Xian Li, Kai-Ming Li, Tao Li, Yan-Song Liu, Zhe-Ning Liu, Yi-Cheng Long, Bin Lu, Qing-Hua Luo, Hua-Qing Meng, Dai-Hui Peng, Hai-Tang Qiu, Jiang Qiu, Yue-Di Shen, Yu-Shu Shi, Tian-Mei Si, Yan-Qing Tang, Chuan-Yue Wang, Fei Wang, Kai Wang, Li Wang, Xiang Wang, Ying Wang, Yu-Wei Wang, Xiao-Ping Wu, Xin-Ran Wu, Chun-Ming Xie, Guang-Rong Xie, Hai-Yan Xie, Peng Xie, Xiu-Feng Xu, Hong Yang, Jian Yang, Jia-Shu Yao, Shu-Qiao Yao, Ying-Ying Yin, Yong-Gui Yuan, Yu-Feng Zang, Ai-Xia Zhang, Hong Zhang, Ke-Rang Zhang, Lei Zhang, Zhi-Jun Zhang, Jing-Ping Zhao, Ru-Bai Zhou, Yi-Ting Zhou, Jun-Juan Zhu, Zhi-Chen Zhu, Chao-Jie Zou, Xi-Nian Zuo, Chao-Gan Yan, Wen-Bin Guo

Publikováno v: Translational Psychiatry, Vol 12, Iss 1, Pp 1-9 (2022)

Abstract The nucleus accumbens (NAc) is considered a hub of reward processing and a growing body of evidence has suggested its crucial role in the pathophysiology of major depressive disorder (MDD). However, inconsistent results have been reported by

Externí odkaz: https://doaj.org/article/9d20cf1f719342a0b44bb2e78b8508ff

Disrupted intrinsic functional brain topology in patients with major depressive disorder

Autor: Yan Qing Tang, Qiyong Gong, Hai Tang Qiu, Yu Wei Wang, Xi Long Cui, Xiang Wang, Hai Yan Xie, Zhijun Zhang, Tian-Mei Si, Xue Ying Li, Jing Ping Zhao, Yu Shu Shi, Yi-Ting Zhou, Lan Hu, Yan Song Liu, Chun Ming Xie, Kaiming Li, Ai Xia Zhang, Jiang Qiu, Bin Lu, Wei Chen, Yiru Fang, Lei Zhang, Tao Li, Xiao Ping Wu, Li Wang, Zhe Ning Liu, Hong Yang, Francisco X. Castellanos, Qi Jing Bo, Kai Wang, Jia Duan, Ru-Bai Zhou, Zheng Hua Hou, Xiu Feng Xu, Hui Xian Li, Guan Mao Chen, Chao Jie Zou, Yu Qi Cheng, Yong Gui Yuan, Xinran Wu, Hua Qing Meng, Shu Qiao Yao, Chuanyue Wang, Yu-Feng Zang, Ke Rang Zhang, Guang Rong Xie, Peng Xie, Yue di Shen, Xiao Chen, Fei Wang, Jian Yang, Yi Cheng Long, Li Kuang, Ning Xuan Chen, Tong Jian Bai, Chang Cheng, Wenbin Guo, Qing Hua Luo, Jun Juan Zhu, Ying Ying Yin, Jun Cao, Jia Shu Yao, Feng Li, Zhi Chen Zhu, Le Li, Xi-Nian Zuo, Daihui Peng, Chao-Gan Yan, Ying Wang, Zuo Bing Chen, Hong Zhang, Zhi Kai Chang

Publikováno v: Molecular Psychiatry. 26:7363-7371

Aberrant topological organization of whole-brain networks has been inconsistently reported in studies of patients with major depressive disorder (MDD), reflecting limited sample sizes. To address this issue, we utilized a big data sample of MDD patie

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::60713bda57d5186647eee354a7b48d51
https://doi.org/10.1038/s41380-021-01247-2

A Practical Alzheimer Disease Classifier via Brain Imaging-Based Deep Learning on 85,721 Samples

Autor: Xue-Ying Li, Ning-Xuan Chen, Le Li, Bin Lu, Hui-Xia Zhou, Xiao Chen, Shi-Xian Cui, Paul M. Thompson, Zhen Fan, Yu-Wei Wang, Hong Yang, Zhi-Chen Zhu, Chao-Gan Yan, Zhao-Yu Deng, Francisco X. Castellanos, Zhi-Kai Chang, Hui-Xian Li

BackgroundBeyond detecting brain lesions or tumors, comparatively little success has been attained in identifying brain disorders such as Alzheimer’s disease (AD), based on magnetic resonance imaging (MRI). Many machine learning algorithms to detec

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::57675a793522c720f6a22a6ce67d6f24
https://doi.org/10.1101/2020.08.18.256594

Measurement Model and Simulation of Soil Nitrate Nitrogen Based on Ion Selective Electrode

Autor: Shang Feng Du, Li Zhang, Zhi Kai Chang

Publikováno v: Advanced Materials Research. :657-662

The existing conventional detection methods ofnitrate nitrogenmostly consume time, cost a lot of moneyand need professionals. This limits the application of soil testing and fertilization technology at the grass-roots level. Therefore, a kind of fast

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::053a79e95b7afd6dc6c63acf6730102b
https://doi.org/10.4028/www.scientific.net/amr.718-720.657